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DBMS > Badger vs. Datastax Enterprise vs. Ignite vs. Microsoft Azure Data Explorer

System Properties Comparison Badger vs. Datastax Enterprise vs. Ignite vs. Microsoft Azure Data Explorer

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Editorial information provided by DB-Engines
NameBadger  Xexclude from comparisonDatastax Enterprise  Xexclude from comparisonIgnite  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparison
DescriptionAn embeddable, persistent, simple and fast Key-Value Store, written purely in Go.DataStax Enterprise (DSE) is the always-on, scalable data platform built on Apache Cassandra and designed for hybrid Cloud. DSE integrates graph, search, analytics, administration, developer tooling, and monitoring into a unified platform.Apache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.Fully managed big data interactive analytics platform
Primary database modelKey-value storeWide column storeKey-value store
Relational DBMS
Relational DBMS infocolumn oriented
Secondary database modelsDocument store
Graph DBMS
Spatial DBMS
Search engine
Vector DBMS
Document store infoIf a column is of type dynamic docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-types/­dynamic then it's possible to add arbitrary JSON documents in this cell
Event Store infothis is the general usage pattern at Microsoft. Billing, Logs, Telemetry events are stored in ADX and the state of an individual entity is defined by the arg_max(timestamps)
Spatial DBMS
Search engine infosupport for complex search expressions docs.microsoft.com/­en-us/­azure/­kusto/­query/­parseoperator FTS, Geospatial docs.microsoft.com/­en-us/­azure/­kusto/­query/­geo-point-to-geohash-function distributed search -> ADX acts as a distributed search engine
Time Series DBMS infosee docs.microsoft.com/­en-us/­azure/­data-explorer/­time-series-analysis
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.20
Rank#325  Overall
#49  Key-value stores
Score6.31
Rank#57  Overall
#4  Wide column stores
Score3.64
Rank#89  Overall
#13  Key-value stores
#48  Relational DBMS
Score5.16
Rank#69  Overall
#37  Relational DBMS
Websitegithub.com/­dgraph-io/­badgerwww.datastax.com/­products/­datastax-enterpriseignite.apache.orgazure.microsoft.com/­services/­data-explorer
Technical documentationgodoc.org/­github.com/­dgraph-io/­badgerdocs.datastax.comapacheignite.readme.io/­docsdocs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperDGraph LabsDataStaxApache Software FoundationMicrosoft
Initial release2017201120152019
Current release6.8, April 2020Apache Ignite 2.6cloud service with continuous releases
License infoCommercial or Open SourceOpen Source infoApache 2.0commercialOpen Source infoApache 2.0commercial
Cloud-based only infoOnly available as a cloud servicenononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Datastax Astra DB: Astra DB simplifies cloud-native Cassandra application development for your apps, microservices and functions. Deploy in minutes on AWS, Google Cloud, Azure, and have it managed for you by the experts, with serverless, pay-as-you-go pricing.
Implementation languageGoJavaC++, Java, .Net
Server operating systemsBSD
Linux
OS X
Solaris
Windows
Linux
OS X
Linux
OS X
Solaris
Windows
hosted
Data schemeschema-freeschema-freeyesFixed schema with schema-less datatypes (dynamic)
Typing infopredefined data types such as float or datenoyesyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-types
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.nonoyesyes
Secondary indexesnoyesyesall fields are automatically indexed
SQL infoSupport of SQLnoSQL-like DML and DDL statements (CQL); Spark SQLANSI-99 for query and DML statements, subset of DDLKusto Query Language (KQL), SQL subset
APIs and other access methodsProprietary protocol infoCQL (Cassandra Query Language)
TinkerPop Gremlin infowith DSE Graph
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Supported programming languagesGoC
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
C#
C++
Java
PHP
Python
Ruby
Scala
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Server-side scripts infoStored proceduresnonoyes (compute grid and cache interceptors can be used instead)Yes, possible languages: KQL, Python, R
Triggersnoyesyes (cache interceptors and events)yes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicy
Partitioning methods infoMethods for storing different data on different nodesnoneSharding infono "single point of failure"ShardingSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesnoneconfigurable replication factor, datacenter aware, advanced replication for edge computingyes (replicated cache)yes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesyes (compute grid and hadoop accelerator)Spark connector (open source): github.com/­Azure/­azure-kusto-spark
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate Consistency
Tunable Consistency infoconsistency level can be individually decided with each write operation
Immediate ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanono infoAtomicity and isolation are supported for single operationsACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyesno
User concepts infoAccess controlnoAccess rights for users can be defined per objectSecurity Hooks for custom implementationsAzure Active Directory Authentication
More information provided by the system vendor
BadgerDatastax EnterpriseIgniteMicrosoft Azure Data Explorer
Specific characteristicsDataStax Enterprise is scale-out data infrastructure for enterprises that need to...
» more
Competitive advantagesSupporting the following application requirements: Zero downtime - Built on Apache...
» more
Typical application scenariosApplications that must be massively and linearly scalable with 100% uptime and able...
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Key customersCapital One, Cisco, Comcast, eBay, McDonald's, Microsoft, Safeway, Sony, UBS, and...
» more
Market metricsAmong the Forbes 100 Most Innovative Companies, DataStax is trusted by 5 of the top...
» more
Licensing and pricing modelsAnnual subscription
» more

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BadgerDatastax EnterpriseIgniteMicrosoft Azure Data Explorer
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